What can Genie do with dashboards and business data?

Summary

• Genie lets non-technical users ask natural language questions of business data and dashboards, receiving instant answers without writing SQL or navigating complex interfaces.
• Genie layers a semantic understanding of your data (metadata, column definitions, relationships) on top of dashboards and tables, so it can interpret business questions and map them to the right data.
• Core capabilities include natural language search across dashboards, guided exploration of data (drilling, filtering, comparisons), and contextual insights (anomalies, trends) extracted from the data.
• Genie respects data governance: queries are authenticated, audited, and governed by the same access policies that protect your dashboards, so each user only sees data they are authorized for.

What can Genie do with dashboards and business data?
Genie transforms dashboards and business data from static reports into intelligent, conversational interfaces. Instead of hunting through tabs and applying filters, users ask Genie questions in plain English: "What was last month's revenue by region?" or "Show me customers with no activity in the past 30 days." Genie understands the question, queries the underlying data, and responds with tables, charts, or direct answers.
Genie's core strength is bridging the gap between what business users want to know and what data they can access. It sits between your dashboards and your data, learning the semantic relationships (what "revenue" means, which tables hold it, how regions are defined), so it can answer questions that aren't pre-built into the dashboard UI. For organizations with hundreds of tables or dashboards, Genie eliminates the need for users to know the data model.

What Genie can do with dashboards

Genie augments dashboards in three ways:
Instant answers to ad-hoc questions: Users ask Genie questions about the data a dashboard shows. Instead of manually building a new dashboard card or drill-down, they get an instant answer. This is especially useful for questions specific to one user's context ("top customers for my territory", "anomalies in my region's inventory").
Guided exploration: Genie suggests related metrics, drill-downs, and comparisons relevant to what users are already viewing. If a user asks about revenue trends, Genie might suggest breakdowns by product, region, or customer segment, letting users explore without knowing the data model.
Contextual insights: Genie analyzes data in context and surfaces anomalies, trends, or correlations that users might miss. It flags significant changes in key metrics, identifies the regions or segments responsible, and suggests follow-up questions.

Key capabilities to evaluate

When assessing AI/BI tools for data exploration, prioritize these criteria:

Capability	Why it matters
Natural language understanding of your data	The tool should understand your domain language ("net revenue" vs "gross"), not just SQL keywords. Semantic layer quality determines how well it maps business questions to the right data.
Governance and access control	Users should only see dashboards and data they are authorized for. Queries must be audited and logged. The tool should inherit your existing access policies, not bypass them.
Integration with your dashboard tool	Genie should be native to your BI platform, not a separate tool. Disconnected AI requires context switching and manual data transfer.
Accuracy and explainability	When Genie generates a query or insight, users should understand what data it queried and why. Unexplained or inaccurate answers undermine trust.
Performance at scale	Ad-hoc natural language queries can be resource-intensive. The tool should handle large datasets and concurrent users without degrading response time.
Ability to add domain context	Your team should be able to teach Genie about your metrics, definitions, and relationships so it improves over time. Static models that can't learn become stale.

How Genie approaches AI/BI

Genie is built as a native layer on Databricks dashboards and business data, powered by a semantic understanding of your tables, columns, and relationships. When you ask Genie a question, it:

1. Parses your question in plain English, identifying the metrics, dimensions, and filters you're asking for.
2. Maps to your data using semantic metadata (column definitions, business terminology, relationships between tables).
3. Respects access control: Genie applies your data governance policies, so it only queries data you are authorized to see.
4. Returns results as a chart, table, or narrative explanation, with full traceability back to the source data.
5. Logs the query for audit and compliance purposes.

Genie also learns from your interactions. If you correct a query or refine a question, Genie improves its semantic model, so future queries are more accurate. The semantic layer is maintained by your data team, not by Genie, giving you control over how your data is understood.

Use cases

Analyst augmentation: Analysts spend time manually answering ad-hoc business questions. Genie answers routine questions instantly, so analysts focus on deeper analysis and investigation.
Self-service BI for non-technical users: Executives and business managers can explore data without SQL knowledge or dashboard training. Genie is their interface to data.
Compliance and audit: When all user queries are logged and traceable, compliance teams have full visibility into who asked what, when, and what data was accessed.
Real-time insights: Genie continuously monitors data for anomalies and trends, surfacing changes before users ask. This is especially useful for operations teams and on-call staff.

FAQs

How does Genie know what my data means?

Genie uses a semantic layer: definitions, column descriptions, and relationships that your data team maintains. For example, if a column is defined as "customer_id" with a relationship to the "customers" table, Genie knows that filtering by customer is meaningful. The semantic layer is built in Databricks using business semantics, a feature in Databricks that lets your team document data in a governed, discoverable way.

Can Genie answer questions about data I'm not authorized to access?

No. Genie respects your access control policies. If a user can't see a table or column in a dashboard, they can't query it via Genie. All queries are authenticated and logged.

Does Genie work with any BI tool, or only Databricks?

Genie is built natively into Databricks dashboards and the Databricks AI/BI platform. It works best with Databricks data because it integrates directly with the semantic layer and access control. Integrations with third-party BI tools are possible but require additional setup.

What happens if Genie gives an incorrect answer?

Genie is deterministic: it writes SQL queries, which either return the correct data or don't. Inaccuracy usually stems from unclear questions or incomplete semantic metadata. If a question is ambiguous, Genie asks for clarification. If Genie consistently misunderstands a metric, your data team can improve the semantic definitions.